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Items: 1 to 20 of 99

1.

High-Dimensional Heteroscedastic Regression with an Application to eQTL Data Analysis.

Daye ZJ, Chen J, Li H.

Biometrics. 2012 Mar;68(1):316-326. Epub 2011 Aug 12.

2.

A regularized multivariate regression approach for eQTL analysis.

Wang X, Qin L, Zhang H, Zhang Y, Hsu L, Wang P.

Stat Biosci. 2015 May 1;7(1):129-146.

PMID:
26085849
3.

Accounting for Uncertainty in Heteroscedasticity in Nonlinear Regression.

Lim C, Sen PK, Peddada SD.

J Stat Plan Inference. 2012 May 1;142(5):1047-1062.

4.

Network-based group variable selection for detecting expression quantitative trait loci (eQTL).

Wang W, Zhang X.

BMC Bioinformatics. 2011 Jun 30;12:269. doi: 10.1186/1471-2105-12-269.

5.

Regression calibration with heteroscedastic error variance.

Spiegelman D, Logan R, Grove D.

Int J Biostat. 2011;7(1):4. doi: 10.2202/1557-4679.1259. Epub 2011 Jan 6.

6.

Robust nonlinear regression in applications.

Lim C, Sen PK, Peddada SD.

J Indian Soc Agric Stat. 2013;67(2):215-234.

7.

NETWORK-REGULARIZED HIGH-DIMENSIONAL COX REGRESSION FOR ANALYSIS OF GENOMIC DATA.

Sun H, Lin W, Feng R, Li H.

Stat Sin. 2014 Jul;24(3):1433-1459.

8.
9.
10.

Joint high-dimensional Bayesian variable and covariance selection with an application to eQTL analysis.

Bhadra A, Mallick BK.

Biometrics. 2013 Jun;69(2):447-57. doi: 10.1111/biom.12021. Epub 2013 Apr 22.

PMID:
23607608
11.

Expression quantitative trait loci mapping with multivariate sparse partial least squares regression.

Chun H, Keles S.

Genetics. 2009 May;182(1):79-90. doi: 10.1534/genetics.109.100362. Epub 2009 Mar 6.

12.
13.

Algorithms for robust nonlinear regression with heteroscedastic errors.

Tóthfalusi L, Endrényi L.

Int J Biomed Comput. 1996 Aug;42(3):181-90.

PMID:
8894774
14.

An information-theoretic machine learning approach to expression QTL analysis.

Huang T, Cai YD.

PLoS One. 2013 Jun 25;8(6):e67899. doi: 10.1371/journal.pone.0067899. Print 2013.

15.
16.

Robust Linear Models for Cis-eQTL Analysis.

Rantalainen M, Lindgren CM, Holmes CC.

PLoS One. 2015 May 18;10(5):e0127882. doi: 10.1371/journal.pone.0127882. eCollection 2015.

17.

Bayesian Semiparametric Density Deconvolution in the Presence of Conditionally Heteroscedastic Measurement Errors.

Sarkar A, Mallick BK, Staudenmayer J, Pati D, Carroll RJ.

J Comput Graph Stat. 2014 Oct 1;23(4):1101-1125.

18.

Local polynomial estimation of heteroscedasticity in a multivariate linear regression model and its applications in economics.

Su L, Zhao Y, Yan T, Li F.

PLoS One. 2012;7(9):e43719. doi: 10.1371/journal.pone.0043719. Epub 2012 Sep 17. Erratum in: PLoS One. 2012;7(11). doi:10.1371/annotation/01ebf0b5-ccd3-494d-b577-170981f7bc36.

19.

A Bayesian partition method for detecting pleiotropic and epistatic eQTL modules.

Zhang W, Zhu J, Schadt EE, Liu JS.

PLoS Comput Biol. 2010 Jan 15;6(1):e1000642. doi: 10.1371/journal.pcbi.1000642.

20.

Variance estimation in the analysis of microarray data.

Wang Y, Ma Y, Carroll RJ.

J R Stat Soc Series B Stat Methodol. 2009 Apr 1;71(2):425-445.

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